Operations Research

最新文章

• Mallows-Smoothed Distribution over Rankings Approach for Modeling Choice AI翻译
  作者：Desir, Antoine; Goyal, Vineet; Jagabathula, Srikanth; Segev, Danny
  作者单位：INSEAD Business School; Columbia University; New York University; Tel Aviv University
  摘要：Assortment optimization is an important problem arising in many applications, including retailing and online advertising. The goal in such problems is to determine a revenue-/profit-maximizing subset of products to offer from a large universe of products when customers exhibit stochastic substitution behavior. We consider a mixture of Mallows model for demand, which can be viewed as a smoothed generalization of sparse, rank-based choice models, designed to overcome some of their key limitation...
• Technical Note-Consumer Choice and Market Expansion: Modeling, Optimization, and Estimation AI翻译
  作者：Wang, Ruxian
  作者单位：Johns Hopkins University
  摘要：Market size, measured by the number of people who are interested in products from the same category, may be largely influenced by assortment planning and pricing decisions. This effect is referred to as market expansion. In this paper, I incorporate the market expansion effects into consumer choice models and investigate various operations problems. In particular, I take the widely used multinomial logit model as a showcase to examine the market expansion effects on assortment planning and pri...
• Timing It Right: Balancing Inpatient Congestion vs. Readmission Risk at Discharge AI翻译
  作者：Shi, Pengyi; Helm, Jonathan E.; Deglise-Hawkinson, Jivan; Pan, Julian
  作者单位：Purdue University System; Purdue University; Indiana University System; IU Kelley School of Business; Indiana University Bloomington
  摘要：When to discharge a patient plays an important role in hospital patient flow management and the quality of care and patient outcomes. In this work, we develop and implement a data-integrated decision support framework to aid hospitals in managing the delicate balance between readmission risk at discharge and ward congestion. We formulate a large-scale Markov decision process (MDP) that integrates a personalized readmission prediction model to dynamically prescribe both how many and which patie...
• Asymmetric Multidepot Vehicle Routing Problems: Valid Inequalities and a Branch-and-Cut Algorithm AI翻译
  作者：Broek, Michiel A. J. Uit Het; Schrotenboer, Albert H.; Jargalsaikhan, Bolor; Roodbergen, Kees Jan; Coelho, Leandro C.
  作者单位：University of Groningen; Laval University; Laval University
  摘要：We present a generic branch-and-cut framework for solving routing problems with multiple depots and asymmetric cost structures, which determines a set of cost-minimizing (capacitated) vehicle tours that fulfill a set of customer demands. The backbone of the framework is a series of valid inequalities with corresponding separation algorithms that exploit the asymmetric cost structure in directed graphs. We derive three new classes of so-called D-k inequalities that eliminate subtours, enforce t...
• Credit Risk: Simple Closed-Form Approximate Maximum Likelihood Estimator AI翻译
  作者：Deo, Anand; Juneja, Sandeep
  作者单位：Tata Institute of Fundamental Research (TIFR)
  摘要：We consider discrete default intensity-based and logit-type reduced-form models for conditional default probabilities for corporate loans where we develop simple closed-form approximations to the maximum likelihood estimator (MLE) when the underlying covariates follow a stationary Gaussian process. In a practical asymptotic regime where the default probabilities are small, say less than 3% annually, and the number of firms and the time period of data available are reasonably large, we rigorous...
• Nonadditive Multiattribute Utility Functions for Portfolio Decision Analysis AI翻译
  作者：Liesio, Juuso; Vilkkumaa, Eeva
  作者单位：Aalto University
  摘要：Portfolio decision analysis models support selecting a portfolio of projects in view of multiple objectives and limited resources. In applications, portfolio utility is commonly modeled as the sum of the projects' multiattribute utilities, although such approaches lack rigorous decision-theoretic justification. This paper establishes the axiomatic foundations of a more general class of multilinear portfolio utility functions, which includes additive and multiplicative portfolio utility functio...
• Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions AI翻译
  作者：Golrezaei, Negin; Javanmard, Adel; Mirrokni, Vahab
  作者单位：Massachusetts Institute of Technology (MIT); University of Southern California; Alphabet Inc.; Google Incorporated
  摘要：Motivated by pricing in ad exchange markets, we consider the problem of robust learning of reserve prices against strategic buyers in repeated contextual second-price auctions. Buyers' valuations for an item depend on the context that describes the item. However, the seller is not aware of the relationship between the context and buyers' valuations (i.e., buyers' preferences). The seller's goal is to design a learning policy to set reserve prices via observing the past sales data, and her obje...
• Optimistic Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds AI翻译
  作者：Jiang, Daniel R.; Al-Kanj, Lina; Powell, Warren B.
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Princeton University
  摘要：Monte Carlo tree search (MCTS), most famously used in game-play artificial intelligence (e.g., the game of Go), is a well-known strategy for constructing approximate solutions to sequential decision problems. Its primary innovation is the use of a heuristic, known as a default policy, to obtain Monte Carlo estimates of downstream values for states in a decision tree. This information is used to iteratively expand the tree toward regions of states and actions that an optimal policy might visit....
• Production Scheduling for Strategic Open Pit Mine Planning: A Mixed-Integer Programming Approach AI翻译
  作者：Rivera Letelier, Orlando; Espinoza, Daniel; Goycoolea, Marcos; Moreno, Eduardo; Munoz, Gonzalo
  作者单位：Universidad Adolfo Ibanez; Alphabet Inc.; Google Incorporated; Universidad Adolfo Ibanez; Universidad Adolfo Ibanez; Universidad de O'Higgins
  摘要：Given a discretized representation of an ore body known as a block model, the open pit mining production scheduling problem that we consider consists of defining which blocks to extract, when to extract them, and how or whether to process them, in such a way as to comply with operational constraints and maximize net present value. Although it has been established that this problem can be modeled with mixed-integer programming, the number of blocks used to represent real-world mines (millions) ...
• Pricing and Assortment Strategies with Product Exchanges AI翻译
  作者：Wagner, Laura; Martinez-de-Albeniz, Victor
  作者单位：Universidade Catolica Portuguesa; University of Navarra; IESE Business School
  摘要：Lenient return policies enable consumers to return or exchange products they are unsatisfied with, which boosts sales. Unfortunately, they also increase retailer costs. We develop a search framework where consumers sequentially learn about products' true value and evaluate whether to keep, exchange, or return them. Our formulation results in a tractable attraction demand model that can be used for optimization. We show that when pricing is not a decision, the assortment problem does not have a...